Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
In this paper, we present several algorithms for performing all-to-many personalized communication on distributed memory parallel machines. We assume that each processor sends a different message (of potentially different size) to a subset of all the processors involved in the collective communication. The algorithms are based on decomposing the communication matrix into a set of partial permutations. We study the effectiveness of our algorithms from both the view of static scheduling and runtime scheduling. © 1995 Academic Press, Inc.
Arnon Amir, Michael Lindenbaum
IEEE Transactions on Pattern Analysis and Machine Intelligence
Arthur Nádas
IEEE Transactions on Neural Networks
Ken C.L. Wong, Satyananda Kashyap, et al.
Pattern Recognition Letters
S. Winograd
Journal of the ACM